Akash Notebooks

[M10-AI]

TL;DR

Akash Notebooks (AKN) is an online platform for data science and machine learning where users can train models, compete with models, share datasets and collaborate on projects.
Think Kaggle or Google Colab, but powered by Akash Network. The solution is meant to abstract the complexity, enabling advanced GPU-accelerated development where you pay-as-you-go. In addition, the competitions feature primes Akash Notebooks to stand out as the platform for AI and DeAI community’s to create and manage competitions.

Moreover Akash Notebooks serves as a community tool for current Insiders programs such as Ringmasters for creating and managing events such as competitions, for potential Akash University Program and for anyone interested in promoting Akash Network.

Motivation

With Akash Network's decentralized compute infrastructure the sky is the limit. Even so the onboarding experience can still feel technically intense, with pre-requisites like dockerization, deployment management, and networking skills. This often impedes data scientists, students, and researchers who lack the DevOps knowledge. Current mainstream alternatives solve this, but offer limited session time, no file system, and inferior hardware with binding subscriptions. This stifles innovation and experimentation beyond simple models.
Akash Notebooks addresses this gap by offering a user interface for long-form model training, code access, and a community-driven competitions ecosystem. The goal is to significantly lower the barrier to entry for leveraging Akash's GPU compute and attract a wider audience to Akash Network.

Technical Description

Akash Notebooks consists of the following components:

• Dockerized Jupyter Lab Instance: A forked and branded version of Jupyter Lab customized for Akash Notebooks, packaged in a container with GPU access.
• Integration with GitHub: Allowing users to automatically load their GitHub code into Jupyter Lab as it is deployed to get started immediately.
• Deployment Dashboard GUI: A web-based frontend that abstracts Akash SDL and deployment management, enabling users to launch and manage compute jobs without CLI or YAML configurations.
• Filesystem Integration: The platform integrates with users' GitHub repositories and exposes them through a drag-and-drop folder UI mimicking a traditional OS environment.
• VS Code Support: Enables opening Jupyter Lab instances within the user's local VS Code setup for a familiar development experience.
• Persistent Session Management: Users fund deployments directly, allowing them to run long training sessions uninterrupted as opposed to time-limited sessions on competing platforms.
• Event Management Module: A database and API backend powers an event section.
• Dataset and Pipeline Service: Users can create a pipeline that reads a dataset, processes or transforms it, and outputs a new version of the dataset. This enables reproducible and shareable data transformation workflows.

Current Status

A minimal viable product (MVP) of Akash Notebooks has been built with 2-3 core features which will be presented through a demo video one week from posting this discussion. The open-source license for the project is still to be determined. Once a future proposal is approved and application is complete, we will open-source the GitHub repository.
Authentication & Payments
Users can authenticate using either their Keplr wallet, GitHub OAuth or Email. Users may choose to fund their deployments in either AKT or USD, accommodating both crypto-native and traditional users.

Target Audience

The initial focus is on individuals such as students, researchers, data scientists, and independent ML engineers. However, the platform’s aim is to pivot toward team and organisational use cases.

Benefits to Akash Network

• Increased Akash Network Utilization: Encourages broader use of Akash Network resources by making them more accessible.
• Expanded User Base: Opens Akash Network to non-developers such as data scientists, researchers, students, and startups.
• Improved Brand Visibility: Acts as a community tool for Ringmasters and potential Akash Insiders University Program to run workshops or competitions.
• Provider Incentives: Increases opportunity for providers to monetize Akash Network.
• Support for Open Source: Reinforces Akash Network’s commitment to open and decentralized systems.

Open Questions / Request for Feedback

• What would be the best way to encourage community contributions to this open-source project?
• How to best monetize the app to make it self-sustained?
• How soon should we strive to integrate FIAT?

Stay tuned for demo video!
HardBoiledEggs
Akash Insider
M10 AI